Paper
20 May 2006 Binary Cr etch process control directed at the 45nm node
Author Affiliations +
Abstract
In any plasma etch process, there are slight variations in the output of generators, mass flows, and pressure control systems that may sometimes contribute to run-to-run differences in the final product. Even excluding material differences, endpoint times can vary somewhat, requiring an accurate endpoint system to stop processing at the appropriate time. The most widely accepted systems for plasma endpoint detection are based on optical emission spectroscopy (OES). OES-based endpoint systems analyze the visible and near-visible electromagnetic radiation emitted by the plasma in order to detect subtle changes that occur when a film has been completely etched. A signal can be constructed from this data and used to stop or otherwise modify the process. Other methods exist for detecting endpoint. Laser reflectance is well known to photomask etch engineers, but there are also lesser known methods that depend on detecting changes in pressure, DC bias, or match network positions. Each system has its own unique set of strengths and weaknesses. While all of these systems are quite capable of detecting endpoint under normal circumstances, the requirements of low load photomask etching are extremely demanding. Therefore, a need exists to enhance endpoint detection on low load photomasks. Our proposed method is a multi-sensor system that includes measurements of several process parameters in addition to emission spectra to generate an endpoint signal that is more robust than an endpoint signal produced by a single sensor.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
J. Plumhoff, R. Westerman, and C. Constantine "Binary Cr etch process control directed at the 45nm node", Proc. SPIE 6283, Photomask and Next-Generation Lithography Mask Technology XIII, 62831U (20 May 2006); https://doi.org/10.1117/12.681757
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KEYWORDS
Etching

Chromium

Genetic algorithms

Signal processing

Plasma

Photomasks

Signal to noise ratio

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